Using smart data filters to create multi-threaded profiles

ABSTRACT

Aspects of the disclosure relate to using smart data filters to create multi-threaded profiles. A computing platform may generate a multi-threaded profile corresponding to a user. Thereafter, the computing platform may receive, via the communication interface and from a user device, external event information corresponding to the multi-threaded profile. Then, the computing platform may determine, based on the external event information, a filter bank corresponding to a first thread of the multi-threaded profile. Subsequently, the computing platform may determine, based on the external event information and the filter bank, a time to live parameter corresponding to the external event information. Next, the computing platform may retrieve, from a multi-threaded profile server and based on the multi-threaded profile and the filter bank, first thread information corresponding to the first thread of the multi-threaded profile.

BACKGROUND

Aspects of the disclosure relate to data processing, data mining,filtering data, and extracting and removing of either wanted or unwanteddata from a data source. In particular, one or more aspects of thedisclosure relate to using smart data filters to create multi-threadedprofiles.

In some instances, enterprise systems may receive event informationassociated with various users. As enterprise systems become morecomplex, however, the event information associated with the varioususers across an enterprise user base may increase exponentially.Therefore, it may be difficult for the system to efficiently andeffectively filter and/or otherwise process events for the various usersof the enterprise user base, particularly when also attempting tooptimize for resource usage and network bandwidth consumption of theunderlying computing infrastructure.

SUMMARY

Aspects of the disclosure provide effective, efficient, scalable, andconvenient technical solutions that address and overcome the technicalproblems associated with filtering event data associated with smart dataand multi-threaded profiles in an enterprise computing environment.

In accordance with one or more embodiments, a computing platform havingat least one processor, a memory, and a communication interface maygenerate a multi-threaded profile corresponding to a user. Thereafter,the computing platform may receive, via the communication interface andfrom a user device, external event information corresponding to themulti-threaded profile. Then, the computing platform may determine,based on the external event information, a filter bank corresponding toa first thread of the multi-threaded profile. Subsequently, thecomputing platform may determine, based on the external eventinformation and the filter bank, a time to live parameter correspondingto the external event information. Next, the computing platform mayretrieve, from a multi-threaded profile server and based on themulti-threaded profile and the filter bank, first thread informationcorresponding to the first thread of the multi-threaded profile. Then,the computing platform may determine, based on the first threadinformation, the external event information, and the time to liveparameter, one or more recommendations corresponding to the externalevent information. Also, the computing platform may generate one or morecommands directing the user device to display the one or morerecommendations corresponding to the external event information.Subsequently, the computing platform may transmit, via the communicationinterface and to the user device, the one or more commands.

In some embodiments, the computing platform may receive, via thecommunication interface and from an administrative device, new profileinformation corresponding to the multi-threaded profile. Then, thecomputing platform may generate, based on the new profile information, aplurality of threads for the multi-threaded profile, wherein each of theplurality of threads indicates previous interactions corresponding tothe user. In some embodiments, the plurality of threads may comprise aneducation thread, a leisure thread, a hobby thread, or an exchangethread.

In some embodiments, the computing platform may receive, via thecommunication interface and from an external data source, customizationinformation corresponding to the user. Subsequently, the computingplatform may update, based on the customization information, themulti-threaded profile corresponding to the user. In some embodiments,the customization information may comprise social media information orprofessional worksite information corresponding to the user. In someembodiments, the first thread of the multi-threaded profile may comprisean education thread, a leisure thread, a hobby thread, or an exchangethread. In some embodiments, the determining the one or morerecommendations may be based on comparing the first thread informationwith the external event information.

In some embodiments, in response to determining that the time to liveparameter corresponding to the external event information has elapsed,the computing platform may remove the external event information fromthe multi-threaded profile. In some embodiments, the computing platformmay update, based on the external event information, the first threadinformation corresponding to the first thread of the multi-threadedprofile.

In some embodiments, the computing platform may receive, via thecommunication interface and from the user device, second external eventinformation corresponding to the multi-threaded profile. Thereafter, thecomputing platform may determine, based on the second external eventinformation, the filter bank corresponding to the first thread of themulti-threaded profile. Then, the computing platform may determine,based on the second external event information and the filter bank, asecond time to live parameter corresponding to the second external eventinformation. After, the computing platform may retrieve, from themulti-threaded profile server and based on the multi-threaded profileand the filter bank, the first thread information corresponding to thefirst thread of the multi-threaded profile, and the first threadinformation may include the external event information. Subsequently,the computing platform may determine, based on the first threadinformation, the second external event information, and the second timeto live parameter, one or more second recommendations corresponding tothe second external event information. Next, the computing platform maygenerate one or more second commands directing the user device todisplay the one or more second recommendations corresponding to thesecond external event information. Then, the computing platform maytransmit, via the communication interface and to the user device, theone or more second commands.

These features, along with many others, are discussed in greater detailbelow.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure is illustrated by way of example and not limitedin the accompanying figures in which like reference numerals indicatesimilar elements and in which:

FIGS. 1A and 1B depict an illustrative computing environment for usingsmart data filters to create multi-threaded profiles in accordance withone or more example embodiments;

FIGS. 2A, 2B, 2C, 2D, and 2E depict an illustrative event sequence forusing smart data filters to create multi-threaded profiles in accordancewith one or more example embodiments;

FIGS. 3 and 4 depict example graphical user interfaces for using smartdata filters to create multi-threaded profiles in accordance with one ormore example embodiments; and

FIG. 5 depicts an illustrative method for using smart data filters tocreate multi-threaded profiles in accordance with one or more exampleembodiments.

DETAILED DESCRIPTION

In the following description of various illustrative embodiments,reference is made to the accompanying drawings, which form a parthereof, and in which is shown, by way of illustration, variousembodiments in which aspects of the disclosure may be practiced. It isto be understood that other embodiments may be utilized, and structuraland functional modifications may be made, without departing from thescope of the present disclosure.

It is noted that various connections between elements are discussed inthe following description. It is noted that these connections aregeneral and, unless specified otherwise, may be direct or indirect,wired or wireless, and that the specification is not intended to belimiting in this respect.

FIGS. 1A and 1B depict an illustrative computing environment for usingsmart data filters to create multi-threaded profiles in accordance withone or more example embodiments. Referring to FIG. 1A, computingenvironment 100 may include one or more computing devices and/or othercomputer systems. For example, computing environment 100 may include asmart data filter computing platform 110, a multi-threaded profileserver 120, an external data source 130, a user device 140, and anadministrative device 150.

Smart data filter computing platform 110 may be configured to use smartdata filters to create multi-threaded profiles by controlling and/ordirecting actions of other devices and/or computer systems, and/or maybe configured to perform other functions, as discussed in greater detailbelow. In some instances, the smart data filter computing platform 110may perform and/or provide one or more techniques to use smart datafilters to create multi-threaded profiles.

Multi-threaded profile server 120 may be configured to store, maintain,and/or analyze multi-threaded profiles for a plurality of differentusers. For example, the multi-threaded profile server 120 may beconfigured to store and/or maintain multi-threaded profiles for anenterprise organization. The multi-threaded profiles may be associatedwith a plurality of users, clients, and/or entities. For example, somemulti-threaded profiles may be associated with users and/or clientsusing one or more services provided by an enterprise organization.Further, some multi-threaded profiles may be associated with entitiesusing one or more services provided by the enterprise organization. Insome instances, the multi-threaded profile server 120 might not beanother computer system, but the functionalities of the multi-threadedprofile server 120 may be included within the smart data filtercomputing platform 110.

External data source 130 may be a computing system configured to provideevent data to the computing environment 100. For example, the externaldata source 130 may provide external profile information and/or externalevent information. In some instances, the external data source 130 mayprovide external profile information for one or more users. Forinstance, the external data source 130 may be a social media server. Thesocial media server may provide social media information, such asinformation identifying a user's preferences, hobbies, leisureactivities, and/or additional social media information, for one or moreusers. The external data source 130 may provide the social mediainformation to the smart data filter computing platform 110.Additionally, and/or alternatively, the smart data filter computingplatform 110 may create, customize, and/or update one or moremulti-threaded profiles based on the social media information. In someexamples, the external data source 130 may provide external eventinformation corresponding to one or more users. For instance, theexternal event information may correspond to a user or customer of anorganization, such as a financial institution. The external eventinformation may indicate the purchasing of one or more items and/orother spending activities for the user. The smart data filter computingplatform 110 may use the external event information to update themulti-threaded profiles. Additionally, and/or alternatively, in someembodiments, the smart data filter computing platform 110 may use theexternal event information to generate and/or otherwise determine one ormore recommendations based on the spending activities for the user.

User device 140 may be configured to be used by one or more users ofcomputing environment 100. For example, the user device 140 may beconfigured to display, present, and/or otherwise provide one or moreuser interfaces that enable users (who may, e.g., be customers of anorganization, such as a financial institution) to provide external eventinformation for a multi-threaded profile. For example, the user device140 may receive, from the one or more users, user input or selections.Further, the user device 140 may send the user input or selections tothe smart data filter computing platform 110 and/or one or more othercomputer systems and/or devices in computing environment 100. The userdevice 140 may receive, from the smart data filter computing platform110 and/or one or more other computer systems and/or devices incomputing environment 100, information or data in response to the userinput or selection. In some instances, the user device 140 may receivenotifications from the smart data filter computing platform 110 and/orone or more other computer systems and/or devices in computingenvironment 100. The notifications may indicate one or morerecommendations that may be based on the external event information.

Administrative device 150 may be configured to be used by one or moreusers and/or administrators of computing environment 100. For example,the administrative device 150 may be configured to display, present,and/or otherwise provide one or more user interfaces that enable users(who may, e.g., be administrators of an organization) to provide newprofile information corresponding to one or more users. For example, theadministrative device 150 may receive, from the one or more users and/oradministrators, user input or selections. Further, the administrativedevice 150 may send the user input or selections to the smart datafilter computing platform 110 and/or one or more other computer systemsand/or devices in computing environment 100. The administrative device150 may receive, from the smart data filter computing platform 110and/or one or more other computer systems and/or devices in computingenvironment 100, information or data in response to the user input orselection.

In one or more arrangements, the multi-threaded profile server 120, theexternal data source 130, the user device 140, and/or the administrativedevice 150 may be any type of computing device capable of providing auser interface, receiving input via the user interface, andcommunicating the received input to one or more other computing devices.For example, the multi-threaded profile server 120, the external datasource 130, the user device 140, and/or the administrative device 150may, in some instances, be and/or include server computers, desktopcomputers, laptop computers, tablet computers, smart phones, or the likethat may include one or more processors, memories, communicationinterfaces, storage devices, and/or other components. As noted above,and as illustrated in greater detail below, any and/or all of themulti-threaded profile server 120, the external data source 130, theuser device 140, and/or the administrative device 150 may, in someinstances, be special-purpose computing devices configured to performspecific functions.

Computing environment 100 also may include one or more computingplatforms. For example, and as noted above, computing environment 100may include the smart data filter computing platform 110. As illustratedin greater detail below, the smart data filter computing platform 110may include one or more computing devices configured to perform one ormore of the functions described herein. For example, the smart datafilter computing platform 110 may include one or more computers (e.g.,laptop computers, desktop computers, servers, server blades, or thelike).

Computing environment 100 also may include one or more networks, whichmay interconnect one or more of the smart data filter computing platform110, the multi-threaded profile server 120, the external data source130, the user device 140, and/or the administrative device 150. Forexample, computing environment 100 may include network 160. Network 160may include one or more sub-networks (e.g., local area networks (LANs),wide area networks (WANs), or the like). For example, network 160 mayinclude a private sub-network that may be associated with a particularorganization (e.g., a corporation, financial institution, educationalinstitution, governmental institution, or the like) and that mayinterconnect one or more computing devices associated with theorganization. For example, the smart data filter computing platform 110,the multi-threaded profile server 120, the external data source 130, theuser device 140, and/or the administrative device 150 may be associatedwith an enterprise organization, and a private sub-network included innetwork 160 and associated with and/or operated by the organization mayinclude one or more networks (e.g., LANs, WANs, virtual private networks(VPNs), or the like) that interconnect the smart data filter computingplatform 110, the multi-threaded profile server 120, the external datasource 130, the user device 140, and/or the administrative device 150.Network 160 also may include a public sub-network that may connect theprivate sub-network and/or one or more computing devices connectedthereto (e.g., the smart data filter computing platform 110, themulti-threaded profile server 120, the external data source 130, theuser device 140, and/or the administrative device 150) with one or morenetworks and/or computing devices that are not associated with theorganization.

Referring to FIG. 1B, the smart data filter computing platform 110 mayinclude one or more processors 111, memory 112, and communicationinterface 116. A data bus may interconnect processor(s) 111, memory 112,and communication interface 116. Communication interface 116 may be anetwork interface configured to support communication between the smartdata filter computing platform 110 and one or more networks (e.g.,network 160). Memory 112 may include one or more program modules havinginstructions that when executed by processor(s) 111 cause the smart datafilter computing platform 110 to perform one or more functions describedherein and/or one or more databases that may store and/or otherwisemaintain information which may be used by such program modules and/orprocessor(s) 111. In some instances, the one or more program modulesand/or databases may be stored by and/or maintained in different memoryunits of the smart data filter computing platform 110 and/or bydifferent computing devices that may form and/or otherwise make up thesmart data filter computing platform 110. For example, memory 112 mayhave, store, and/or include a smart data filter module 113, a smart datafilter database 114, and a machine learning engine 115. The smart datafilter computing platform 110 may include instructions that directand/or cause the smart data filter computing platform 110 to use smartdata filters to create multi-threaded profiles, as discussed in greaterdetail below. The smart data filter database 114 may store informationused by the smart data filter module 113 and/or the smart data filtercomputing platform 110 in using smart data filters to createmulti-threaded profiles, and/or in performing other functions. Machinelearning engine 115 may have instructions that direct and/or cause thesmart data filter computing platform 110 to set, define, and/oriteratively redefine optimization rules, techniques and/or otherparameters used by the smart data filter computing platform 110 and/orother systems in computing environment 100.

FIGS. 2A, 2B, 2C, 2D, and 2E depict an illustrative event sequence forusing smart data filters to create multi-threaded profiles in accordancewith one or more example embodiments. Referring to FIG. 2A, at step 201,the administrative device 150 may receive new profile information. Forexample, at step 201, the administrative device 150 may receive, from auser and/or administrator, user input indicating one or more commands tocreate a new profile for the user. For instance, the user may wish tocreate a profile and/or an account with an enterprise organization, suchas a financial organization. After receiving the user input from theuser and/or administrator, the administrative device 150 may process theuser input to create the new profile. For example, the administrativedevice 150 may transmit the new profile information to the smart datafilter computing platform 110. Then, the smart data filter computingplatform 110 may use the new profile information to the create the newprofile for the user.

Additionally, and/or alternatively, in some instances, the new profileinformation may comprise additional information corresponding to theuser. For instance, the administrative device 150 may display promptsfor the user to input additional information to be associated with thenew profile and/or account. For example, the additional information mayinclude spending information, education information, leisureinformation, and/or hobby information. After displaying the prompts, theadministrative device 150 may receive user input for the additionalinformation (e.g., spending information, education information, leisureinformation, and/or hobby information) for the profile and/or account.

In some examples, the spending information may indicate spending habits,previous purchases, financial goals, and/or other financial informationindicated by the user. For example, the administrative device 150 mayreceive input indicating one or more financial goals, such as aretirement plan, a college fund, and/or a savings plan. For instance,the user may indicate that they would like to save money to purchase anew house or a new television.

In some embodiments, the education information may indicate educationlevel and/or job information for the user. Additionally, and/oralternatively, the spending information and/or the education informationmay indicate personal and/or joint income for the user. In someinstances, the leisure information may indicate leisure activities thatthe user enjoys in their free-time. For example, the administrativedevice 150 may receive input indicating the user enjoys hiking and/ortraveling to tropical destinations. In some examples, the hobbyinformation may indicate hobbies that the user enjoys. For example, theadministrative device 150 may receive input indicating hobbies, such asplaying video games or ice skating, for the user.

In some embodiments, rather than receiving new profile informationcorresponding a user, the new profile information may correspond toanother enterprise organization, such as a corporation or a businessorganization. For example, a business organization may wish to create aprofile and/or an account with the enterprise organization (e.g., thefinancial organization). The administrative device 150 may receiveand/or process input to create a new profile for the businessorganization. Additionally, and/or alternatively, the administrativedevice 150 may receive additional information corresponding to thebusiness organization. For example, the administrative device 150 mayreceive spending information (e.g., spending habits, purchases, sales,financial goals, and/or other financial information) for the businessorganization. For instance, the business organization may seek todetermine a sufficient travel stipend for employees on business trips.The administrative device 150 may receive spending informationcorresponding to previous travel stipends and/or previous businesstrips. Then, in the steps below, the smart data filter computingplatform 110 may calculate, monitor, and/or update the travel stipendsfor employees of the business organization.

At step 202, the administrative device 150 may transmit new profileinformation to the smart data filter computing platform 110. Forexample, after the administrative device 150 receives the new profileinformation at step 201, the administrative device 150 may transmit thenew profile information to the smart data filter computing platform 110.

At step 203, the smart data filter computing platform 110 may generate anew profile. For example, based on the user input received at step 201,the smart data filter computing platform 110 may generate a new profilefor the user and/or entity. The new profile may include a plurality ofthreads, such as an education thread, an exchange thread, a leisurethread, and/or a hobby thread. As described in more detail below, thesmart data filter computing platform 110 may store and/or populate eachof the plurality of threads with information corresponding to the user.Additionally, and/or alternatively, the smart data filter computingplatform 110 may generate notifications and/or recommendations for theuser based on the plurality of threads.

At step 204, the smart data filter computing platform 110 may categorizethe new profile information. For example, based on the new profileinformation, the smart data filter computing platform 110 may categorizethe new profile information for the new profile created at step 203. Forinstance, as mentioned previously, the new profile information mayinclude additional information (e.g., spending information, educationinformation, leisure information, and/or hobby information) for theprofile and/or account. The smart data filter computing platform 110 mayparse and categorize the additional information. Afterwards, the smartdata filter computing platform 110 may categorize and store theadditional information in the plurality of threads, such as theeducation thread, the exchange thread, the leisure thread, and/or thehobby thread, for the new profile.

In some instances, the smart data filter computing platform 110 mayparse through the additional information to identify educationinformation for the new profile. For example, the education informationmay indicate that the user is a recent college graduate and has a newjob. Then, the smart data filter computing platform 110 may categorizeand/or store the education information (e.g., the user is a recentcollege graduate and has a new job) in the education thread.Additionally, and/or alternatively, the smart data filter computingplatform 110 may parse through the additional information to identifythe spending information, the leisure information, and/or the hobbyinformation. For example, the spending information may indicate that theuser has a financial goal (e.g., a retirement plan) and/or is saving topurchase an item (e.g., a new television). Additionally, and/oralternatively, the leisure information may indicate the user enjoystaking vacations to tropical destinations. After parsing through theadditional information, the smart data filter computing platform 110 maycategorize and/or store the spending information in the exchange thread,the leisure information in the leisure thread, and/or the hobbyinformation in the hobby thread.

Referring to FIG. 2B, at step 205, the smart data filter computingplatform 110 may determine similar profiles based on the plurality ofthreads. For example, after categorizing the new profile informationinto the plurality of threads, the smart data filter computing platform110 may determine similar profiles to the new profile. Then, the smartdata filter computing platform 110 may retrieve information from thesimilar profiles and store the information in threads of the newprofile. As mentioned previously, the multi-threaded profile server 120may store a plurality of multi-threaded profiles corresponding to aplurality of users and/or entities for the enterprise organization. Eachof the plurality of multi-threaded profiles may include an educationthread, an exchange thread, a leisure thread, and/or a hobby thread.Therefore, the smart data filter computing platform 110 may retrieve,from the multi-threaded profile server 120, information from one or morethreads from one or more similar profiles. After retrieving theinformation, the smart data filter computing platform 110 may store theinformation into the associated thread for the new profile associatedwith the user.

In some examples, the smart data filter computing platform 110 maygenerate and/or transmit commands directing the multi-threaded profileserver 120 to retrieve information from similar profiles to the newprofile. In some embodiments, the multi-threaded profile server 120 mayalready store one or more multi-threaded profiles associated with theuser and/or entity. Thus, the smart data filter computing platform 110may retrieve information from the related profile (e.g., themulti-threaded profile already stored in the multi-threaded profileserver 120) and store the information in the new profile.

In some instances, the smart data filter computing platform 110 may useone or more threads (e.g., the education thread, the exchange thread,the leisure thread, and/or the hobby thread) of the new profile todetermine similar profiles. For example, the education thread of the newprofile may indicate that the user is a recent college graduate. Thus,the smart data filter computing platform 110 may retrieve, from themulti-threaded profile server 120, information from profiles for otherusers that are recent college graduates. The retrieved information mayinclude spending information (e.g., information from the exchangethread). For instance, the smart data filter computing platform 110 mayretrieve previous purchases for other recent college graduates, and maythen store the previous purchases in the exchange thread for the newprofile.

Further, in some examples, the education thread of the new profile mayindicate that the user has a master of business administration (MBA)degree. Additionally, the exchange thread of the new profile mayindicate that the user has set up a retirement plan with the enterpriseorganization. Thus, the smart data filter computing platform 110 mayretrieve, from the multi-threaded profile server 120, information fromprofiles for other users that have an MBA degree and have a similarretirement plan to the user. For instance, the smart data filtercomputing platform 110 may retrieve previous purchases for the similarprofiles, and may then store the previous purchases in the exchangethread for the new profile.

In some embodiments, the education thread of the new profile mayindicate that the user desires to become a full-time writer. Thus, thesmart data filter computing platform 110 may retrieve, from themulti-threaded profile server 120, information from profiles for otherusers that are writers. Additionally, and/or alternatively, the smartdata filter computing platform 110 may retrieve profiles for well-knownor successful writers. Further, the smart data filter computing platform110 may compare the threads for the retrieved profiles to determinesimilarities (e.g., spending activities, leisure activities, hobbies)that are common for well-known or successful writers. Based on thecomparison, the smart data filter computing platform 110 may store thesimilarities in one or more threads of the new profile. For instance,some well-known writers may have similar leisure activities, such asgoing to coffee shops once a week to find inspiration for their work.The smart data filter computing platform 110 may determine thesimilarities (e.g., purchasing a coffee at a coffee shop each week) fromthe retrieved profiles. Then, the smart data filter computing platform110 may store the leisure activity (e.g., going to coffee shops) in theleisure thread for the new profile.

At step 206, the smart data filter computing platform 110 may retrieveexternal profile information from the external data source 130. Forexample, the external data source 130 may be a social media provider.The smart data filter computing platform 110 may retrieve social mediainformation for the user and/or entity. For instance, the smart datafilter computing platform 110 may retrieve social information, such ashobbies, leisure activities, and/or items, for the user. For example,the smart data filter computing platform 110 may retrieve social mediainformation, such as a brand of cars, that the user likes. Further, thesmart data filter computing platform 110 may retrieve hobbies, such ashiking, or leisure activities, such as playing video games, that theuser enjoys.

Additionally, and/or alternatively, the external data source 130 may bea professional worksite. The smart data filter computing platform 110may retrieve, from the external data source 130, professionalinformation for the user. For example, the smart data filter computingplatform 110 may retrieve professional information, such as anoccupation and/or an employer, associated with the user.

At step 207, the smart data filter computing platform 110 may customizethe new profile based on the external profile information. For example,after retrieving the external profile information at step 206, the smartdata filter computing platform 110 may customize the new profile. Insome instances, the smart data filter computing platform 110 may parsethrough the external profile information and categorize the externalprofile information into the plurality of threads (e.g., an educationthread, an exchange thread, a leisure thread, and/or a hobby thread).For instance, the social media information may indicate a brand of carsthat the user likes. The smart data filter computing platform 110 maycategorize and store the brand of cars that the user likes in theexchange thread. Further, the social media information may indicatehobbies, such as hiking, that the user enjoys. The smart data filtercomputing platform 110 may categorize and store the hiking hobby in thehobby thread. Additionally, and/or alternatively, the smart data filtercomputing platform 110 may categorize professional information, such asan occupation, and store the professional information in the exchangethread and/or the education thread.

At step 208, the smart data filter computing platform 110 may store thenew profile in the multi-threaded profile server 120. For example, aftergenerating the new profile, categorizing the new profile informationinto threads, and/or customizing the new profile based on the externalprofile information, the smart data filter computing platform 110 maystore the new profile in the multi-threaded profile server 120. Thus, insome instances, based on the new profile information, the smart datafilter computing platform 110 may generate a pre-built and/or standardprofile for the user. For instance, the user may be a recent collegegraduate, and the smart data filter computing platform 110 may generatea standard recent college graduate profile using the new profileinformation. Then, after generating the standard profile, the smart datafilter computing platform 110 may customize the standard profile for theuser. For example, the smart data filter computing platform 110 may usethe external profile information, such as social media informationassociated with the user, to customize the standard profile for theuser. After generating and/or customizing the profile, the smart datafilter computing platform 110 may store the multi-threaded profile inthe multi-threaded profile server 120. As described below, the smartdata filter computing platform 110 may update and/or optimize themulti-threaded profile based on events for the user. Further, the smartdata filter computing platform 110 may use the multi-threaded profile togenerate notifications and/or recommendations for the user.

In some examples, the smart data filter computing platform 110 maygenerate a plurality of multi-threaded profiles for a plurality of usersand/or entities. After generating each of the plurality ofmulti-threaded profiles, the smart data filter computing platform 110may store these profiles in the multi-threaded profile server 120. Then,as described below, the smart data filter computing platform 110 may usethe multi-threaded profiles to determine recommendations for the userand/or the entity.

FIG. 3 depicts an example graphical user interface for an examplemulti-threaded profile corresponding to a user and/or an entity. Asshown in FIG. 3, graphical user interface 300 may include one or morefields, controls, and/or other elements that may allow a user to viewfeatures of the multi-threaded profile for the user and/or entity. Forexample, the graphical user interface 300 may allow a user to viewthreads for the user profile, such as the “Educational Thread” 310, the“Exchange Thread” 320, the “Leisure Thread” 330, and/or “Hobby Thread”330. The “Educational Thread” 310, the “Exchange Thread” 320, the“Leisure Thread” 330, and/or “Hobby Thread” 330 may be links. Forinstance, after receiving user input for one of the links, such as the“Exchange Thread” 320, the graphical user interface 300 may displayexchange thread information for the user. For example, the graphicaluser interface 300 may display the new profile information, such asfinancial goals, retirement plans, and/or savings information for theuser. Additionally, and/or alternatively, the graphical user interface300 may display exchange thread information for other users with similarprofiles, such as previous purchases that other users have maderecently. Additionally, and/or alternatively, the graphical userinterface 300 may display external profile information, such as a brandof cars that the user likes.

Referring to FIG. 2C, at step 209, the smart data filter computingplatform 110 may receive external event information. For example, thesmart data filter computing platform 110 may receive external eventinformation from the external data source 130, the user device 140,and/or the administrative device 150. In some instances, the externalevent information may be big data corresponding to the enterpriseorganization. For example, the enterprise organization may pursueentrepreneurial endeavors by performing a plurality of services for aplurality of users and/or entities. The enterprise organization may usethe external data source 130, the user device 140, and/or theadministrative device 150 to perform the plurality of services.

In the course of performing the plurality of services, the enterpriseorganization may receive, monitor, track, analyze, process, and/ortransmit a large amount of information, such as big data. For example,while performing services for the enterprise organization, the externaldata source 130, the user device 140, and/or the administrative device150 may transmit information, such as external event information, to thesmart data filter computing platform 110. The external event informationmay be big data (e.g., data sets that are voluminous and complex).Additionally, the enterprise organization may seek to identify importantrelationships within the big data sets. For example, based on the bigdata sets, the enterprise organization may seek to determinerecommendations for a user, such as a client, of the enterpriseorganization. However, due to the complexity of the big data sets, itmay be difficult for the enterprise organization to use the big datasets as is. Thus, prior to using the big data sets, the smart datafilter computing platform 110 may filter the big data sets to generatesmart data. For example, the smart data filter computing platform 110may filter the big data sets to determine relevant data for a particularuser and/or entity. Afterwards, the smart data filter computing platform110 may be able to use the relevant, smart data to determinerecommendations, such as item recommendations, for a particular userand/or entity.

At step 210, the smart data filter computing platform 110 may identifyevents from external event information. For example, as mentioned atstep 209, the smart data filter computing platform 110 may receive bigdata, such as external event information. As the smart data filtercomputing platform 110 receives the external event information, thesmart data filter computing platform 110 may also filter the externalevent information to generate smart data. For instance, many users maybe purchasing items over a period of time, such as on Black Friday.Thus, on Black Friday, the smart data filter computing platform 110 mayreceive external event information indicating a plurality of purchasesfor the plurality of items by the plurality of users. As the smart datafilter computing platform 110 receives the purchase information, thesmart data filter computing platform 110 may also filter the externalevent information into manageable data sets, such as relevant and/orsmart data sets. For instance, at step 210, the smart data filtercomputing platform 110 may identify events, such as individual events,from the external event information. In some examples, the individualevents may be individual purchases and/or transactions for a user. Forexample, on Black Friday, a user may purchase a plurality of items, suchas a television, a tablet, and a smartphone. The smart data filtercomputing platform 110 may filter the external event information toidentify each purchase that the user made.

At step 211, the smart data filter computing platform 110 may retrieve aprofile corresponding to the external event information. For example,after identifying events, such as individual events, from the externalevent information, the smart data filter computing platform 110 mayretrieve a profile, such as a multi-threaded profile, for a user and/orentity corresponding to the event. In some instances, the smart datafilter computing platform 110 may identify purchases made by a user onBlack Friday. The smart data filter computing platform 110 may determinethe user that made the purchases. Then, the smart data filter computingplatform 110 may retrieve a multi-threaded profile, from themulti-threaded profile server 120, for the user.

At step 212, the smart data filter computing platform 110 may determinea filter bank to store the external event information. For example,after retrieving the profile at step 211, the smart data filtercomputing platform 110 may retrieve a multi-threaded profilecorresponding to a user and/or entity. The smart data filter computingplatform 110 may determine a filter bank, such as a thread of themulti-threaded profile, to store the event identified at step 210. Insome examples, the smart data filter computing platform 110 may identifyevents, such as purchases (e.g., television, tablet, smartphone) thatthe user made on Black Friday. At step 212, the smart data filtercomputing platform 110 may determine a filter bank, such as an exchangebank corresponding to the exchange thread of the multi-threaded profile.Then, the smart data filter computing platform 110 may store theidentified events in the corresponding thread. For instance, the smartdata filter computing platform 110 may store the purchases (e.g.,television, tablet, smartphone), in the exchange thread of themulti-threaded profile.

Referring to FIG. 2D, at step 213, the smart data filter computingplatform 110 may determine a time to live parameter. For example, thesmart data filter computing platform 110 may determine a time to liveparameter for the event identified at step 210. The time to liveparameter may be a time limit that the event remains relevant for themulti-threaded profile. After the time to live parameter elapses, thesmart data filter computing platform 110 may remove the event from thethread. For example, the smart data filter computing platform 110 maydetermine an event, such as a purchase of a television, tablet, andsmartphone, on Black Friday. The smart data filter computing platform110 may determine a time to live parameter (e.g., a time limit) for thepurchases. Additionally, and/or alternatively, the smart data filtercomputing platform 110 may determine different time to live parametersfor the different items (e.g., a different time to live parameter foreach of the television, tablet, and smartphone).

In some embodiments, the smart data filter computing platform 110 maydetermine the time to live parameter based on the filter banks. Forexample, each filter bank corresponding to a thread of themulti-threaded profile (e.g., the exchange thread, the education thread,the leisure thread, and/or the hobby thread) may have a different timeto live parameter. For instance, the time to live parameter for theeducation thread (e.g., an MBA degree received by the user) may lastmuch longer than the time to live parameter for the exchange thread(e.g., purchasing a smart phone). For example, the user may replace asmart phone every few years. However, the MBA degree may last forever.Thus, the time to live parameter for the education thread may last muchlonger than the time to live parameter for the exchange thread. In someexamples, the time to live parameter for a hobby, such as hikingoutdoors, may be longer than the time to live parameter for theeducation thread. For instance, the education thread may indicate theuser's occupation. The user may decide to change occupations throughouttheir career. However, the user might always enjoy hiking outdoors.Thus, the time to live parameter for the hobby thread (e.g., hikingoutdoors) may be longer than the time to live parameter for theeducation thread.

At step 214, the smart data filter computing platform 110 may comparethreads of the multi-threaded profile with the event. As mentionedpreviously, the threads of the multi-threaded profile may include aneducation thread, an exchange thread, a hobby thread, and/or a leisurethread. The smart data filter computing platform 110 may compare theevent identified at step 210 with the threads of the multi-threadedprofile.

At step 215, the smart data filter computing platform 110 may identifyrecommendations based on the comparison. For example, based on thecomparison between the threads of the multi-threaded profile with theevent at step 214, the smart data filter computing platform 110 mayidentify recommendations. In some instances, the event may be a purchaseof a television on Black Friday. The multi-threaded profile may indicatethe user has a savings plan or a budget for a television for $500.However, the event may indicate that the user purchased the televisionfor $600 on Black Friday. At step 214, the smart data filter computingplatform 110 may compare the budget that the user indicated for thetelevision for $500 in the exchange thread with the actual price of thetelevision for $600. At step 215 and based on the user exceeding thebudget, the smart data filter computing platform 110 may identifyrecommendations for the user. For instance, Black Friday might not bethe best day to purchase a television. Based on the retrieved profilesfor similar users from step 205, the smart data filter computingplatform 110 may determine that television prices drop after theDecember holidays. Additionally, and/or alternatively, the smart datafilter computing platform 110 may determine that after the Decemberholidays, the television may drop below $500 (e.g., the budget set bythe user). Thus, the smart data filter computing platform 110 identifyone or more recommendations indicating that the user may return thealready purchased television and re-purchase it after the Decemberholidays.

In some examples, the event may indicate that the user purchased a newhouse. The multi-threaded profile may indicate that the user hasrecently graduated college. After comparing the education thread (e.g.,recently graduated college) with the event (e.g., purchasing the newhouse), the smart data filter computing platform 110 may identifyrecommendations for the user, such as item recommendations for the newhouse. For instance, the smart data filter computing platform 110 maydetermine, from the exchange thread of the multi-threaded profile, asavings plan, budget, income, retirement goals, and/or other spendinginformation for the user. Then, based on the exchange thread, the smartdata filter computing platform 110 may identify item recommendations forthe new house. For example, based on a savings plan and/or income of theuser, the smart data filter computing platform 110 may identify washers,dryers, microwaves, refrigerators, and/or other items for the new house.Additionally, and/or alternatively, the smart data filter computingplatform 110 may filter, based on the exchange thread, the items basedon the savings plan, income, and/or other information from the exchangethread. Further, additionally, and/or alternatively, the smart datafilter computing platform 110 may identify item recommendations based onthe retrieved profiles for similar users from step 205. For example, thesmart data filter computing platform 110 may identify itemrecommendations based on other users who have recently graduated collegeand have purchased a new house.

In some embodiments, the event may indicate that the user is seeking topurchase a new car. For example, the user device 140 may transmitexternal event information to the smart data filter computing platform110 indicating that the user is seeking to purchase a new car. Themulti-threaded profile may indicate that the user may like a brand ofcars and may have previously purchased a car from the brand of cars.However, after comparing the multi-threaded profile with the event(e.g., seeking to purchase a new car), the smart data filter computingplatform 110 may identify recommendations for the user, such as carrecommendations for the user. For example, the smart data filtercomputing platform 110 may identify a car recommendation from the samebrand of cars. Further, the smart data filter computing platform 110 mayindicate a best time period (e.g., calendar month), to purchase the newcar. Additionally, and/or alternatively, the smart data filter computingplatform 110 may identify another car brand or another car that may becloser to the user's budget (e.g., determined from the exchange thread).For example, the user may seek to purchase a new car outside of theuser's budget. The smart data filter computing platform 110 maydetermine recommendations that are similar to the new car desired by theuser, but within the budget range of the user. Further, additionally,and/or alternatively, the user may have previously purchased cars from aparticular brand. But, the smart data filter computing platform 110 mayidentify recommendations with similar car brands and/or types to theparticular brand of cars that the user purchased previously.

In some instances, the event may indicate that the user is seeking totravel to a tropical destination. For example, the user device 140 maytransmit external event information to the smart data filter computingplatform 110 indicating that the user is seeking to travel to a tropicaldestination. The multi-threaded profile may indicate that the userfrequently takes these beach trips (e.g., every year or every twoyears). The smart data filter computing platform 110 may identifyrecommendations (e.g., destination spots) for the user. Additionally,and/or alternatively, the smart data filter computing platform 110 maydetermine, from the exchange thread, spending information (e.g., budgetinformation for the user) and may filter the recommendations based onthe spending information.

In some examples, the multi-threaded profile may correspond to anentity, such as an enterprise organization. The event may indicate thatthe enterprise organization is sending one or more employees on abusiness trip. The smart data filter computing platform 110 may identifyrecommendations for the entity. For example, the smart data filtercomputing platform 110 may determine a stipend, such as a dinner and/orhotel budget, for the employees to use on the business trip. Forinstance, the smart data filter computing platform 110 may determine,from the exchange thread of the multi-threaded profile, previous dinnerand/or hotel budgets that employees use for their business trip. Then,the smart data filter computing platform 110 may determine, based on theprevious information (e.g., historical information) of the exchangethread, the stipend to be used by the employees on the business trip.

Additionally, and/or alternatively, the smart data filter computingplatform 110 may determine other dates to send the employees on thebusiness trip. For instance, the smart data filter computing platform110 may determine a more cost-effective date to send employees on abusiness trip. For example, the smart data filter computing platform 110may receive external event information indicating that the enterpriseorganization is sending employees on a business trip to New York fortraining purposes. However, the smart data filter computing platform 110may determine that a music festival is occurring at the same time as thebusiness trip, and hotel prices and/or airplane tickets may increase by20% based on the music festival. Thus, the smart data filter computingplatform 110 may determine a more cost-effective date, such as sendingthe employees on the business trip the week after the music festival,for the business trip.

At step 216, the smart data filter computing platform 110 may generatenotifications based on the recommendations. For example, the smart datafilter computing platform 110 may generate notifications based on therecommendations identified at step 215.

Referring to FIG. 2E, at step 217, the smart data filter computingplatform 110 may transmit the notifications to the user device 140. Forexample, after generating the notifications at step 216, the smart datafilter computing platform 110 may transmit the notifications to the userdevice 140.

FIG. 4 depicts an example graphical user interface for a generatednotification that may be transmitted to the user device 140. As shown inFIG. 4, graphical user interface 400 may include one or more fields,controls, links, and/or other elements that may allow a user to viewnotifications for the recommendations. For example, the graphical userinterface 400 may allow a user to view the “User Profile” 410, the“External Event Information” 420, the “Filter Bank for External Event”430, the “Time to Live Parameter” 440, and/or the “Recommendations” 450.

In some instances, the user device 140 may receive a user input for the“User Profile” 410 link. In response to the user input, the user device140 may display a multi-threaded user profile, such as a multi-threadeduser profile retrieved at step 211. In some examples, the user device140 may receive a user input for the “External Event Information” 420link. In response to the user input, the user device 140 may display anidentified event, such as the events identified at step 210. In someembodiments, the user device 140 may receive a user input for the“Filter Bank for External Event” 430 link. In response to the userinput, the user device 140 may display a filter bank to store theexternal event information, such as the filter bank determined at step212. In some instances, the user device 140 may receive a user input forthe “Time to Live Parameter” 440 link. In response to the user input,the user device 140 may display a time to live parameter, such as thetime to live parameter determined at step 213. In some examples, theuser device 140 may receive a user input for the “Recommendations” 450link. In response to the user input, the user device 140 may displayrecommendations, such as recommendations identified at step 215.

At step 218, the smart data filter computing platform 110 may removeexpired information from the multi-threaded profile. For example, asmentioned previously, the smart data filter computing platform 110 maydetermine time to live parameters for events. At step 218, the smartdata filter computing platform 110 may determine whether any of the timeto live parameters for the multi-threaded profile has elapsed. If a timeto live parameter elapses, the smart data filter computing platform 110may remove the corresponding event from the multi-threaded profile.

At step 219, the smart data filter computing platform 110 may update themulti-threaded profile based on the event. For example, as mentionedpreviously, the smart data filter computing platform 110 may store theidentified event in one or more threads of the multi-threaded profile.Additionally, and/or alternatively, the smart data filter computingplatform 110 may update the multi-threaded profile (e.g., the profileretrieved at step 211) with the recommendations identified at step 215.For instance, the smart data filter computing platform 110 may store therecommendations in one or more threads, such as the exchange thread, ofthe multi-threaded profile. After updating the multi-threaded profilebased on the event, the smart data filter computing platform 110 maytransmit the updated multi-threaded profile to the multi-threadedprofile server 120.

In some embodiments, the smart data filter computing platform 110 mayconsistently and/or periodically filter the external event information.Further, the smart data filter computing platform 110 may also updateand/or store identified events, recommendations, time to liveparameters, and/or other information in the multi-threaded profile. Forexample, as the smart data filter computing platform 110 is receivingthe external event information (e.g., big data), the smart data filtercomputing platform 110 may filter the external event information intoone or more multi-threaded profiles. Then, the smart data filtercomputing platform 110 may use these updated multi-threaded profiles todetermine recommendations and transmit notifications indicating therecommendations to the user device 140. Thus, the smart data filtercomputing platform 110 may filter the big data into smart data sets, andmay use the smart data sets to determine recommendations for aparticular user and/or entity.

FIG. 5 depicts an illustrative method for using smart data filters tocreate multi-threaded profiles in accordance with one or more exampleembodiments. Referring to FIG. 5, at step 505, a computing platformhaving at least one processor, a memory, and a communication interfacemay generate a multi-threaded profile corresponding to a user. At step510, the computing platform may receive, via the communication interfaceand from a user device, external event information corresponding to themulti-threaded profile. At step 515, the computing platform maydetermine, based on the external event information, a filter bankcorresponding to a first thread of the multi-threaded profile. At step520, the computing platform may determine, based on the external eventinformation and the filter bank, a time to live parameter correspondingto the external event information. At step 525, the computing platformmay retrieve, from a multi-threaded profile server and based on themulti-threaded profile and the filter bank, first thread informationcorresponding to the first thread of the multi-threaded profile. At step530, the computing platform may determine, based on the first threadinformation, the external event information, and the time to liveparameter, one or more recommendations corresponding to the externalevent information. At step 535, the computing platform may generate oneor more commands directing the user device to display the one or morerecommendations corresponding to the external event information. At step540, the computing platform may transmit, via the communicationinterface and to the user device, the one or more commands.

One or more aspects of the disclosure may be embodied in computer-usabledata or computer-executable instructions, such as in one or more programmodules, executed by one or more computers or other devices to performthe operations described herein. Generally, program modules includeroutines, programs, objects, components, data structures, and the likethat perform particular tasks or implement particular abstract datatypes when executed by one or more processors in a computer or otherdata processing device. The computer-executable instructions may bestored as computer-readable instructions on a computer-readable mediumsuch as a hard disk, optical disk, removable storage media, solid-statememory, RAM, and the like. The functionality of the program modules maybe combined or distributed as desired in various embodiments. Inaddition, the functionality may be embodied in whole or in part infirmware or hardware equivalents, such as integrated circuits,application-specific integrated circuits (ASICs), field programmablegate arrays (FPGA), and the like. Particular data structures may be usedto more effectively implement one or more aspects of the disclosure, andsuch data structures are contemplated to be within the scope of computerexecutable instructions and computer-usable data described herein.

Various aspects described herein may be embodied as a method, anapparatus, or as one or more computer-readable media storingcomputer-executable instructions. Accordingly, those aspects may takethe form of an entirely hardware embodiment, an entirely softwareembodiment, an entirely firmware embodiment, or an embodiment combiningsoftware, hardware, and firmware aspects in any combination. Inaddition, various signals representing data or events as describedherein may be transferred between a source and a destination in the formof light or electromagnetic waves traveling through signal-conductingmedia such as metal wires, optical fibers, or wireless transmissionmedia (e.g., air or space). In general, the one or morecomputer-readable media may be and/or include one or more non-transitorycomputer-readable media.

As described herein, the various methods and acts may be operativeacross one or more computing servers and one or more networks. Thefunctionality may be distributed in any manner, or may be located in asingle computing device (e.g., a server, a client computer, and thelike). For example, in alternative embodiments, one or more of thecomputing platforms discussed above may be combined into a singlecomputing platform, and the various functions of each computing platformmay be performed by the single computing platform. In such arrangements,any and/or all of the above-discussed communications between computingplatforms may correspond to data being accessed, moved, modified,updated, and/or otherwise used by the single computing platform.Additionally, or alternatively, one or more of the computing platformsdiscussed above may be implemented in one or more virtual machines thatare provided by one or more physical computing devices. In sucharrangements, the various functions of each computing platform may beperformed by the one or more virtual machines, and any and/or all of theabove-discussed communications between computing platforms maycorrespond to data being accessed, moved, modified, updated, and/orotherwise used by the one or more virtual machines.

Aspects of the disclosure have been described in terms of illustrativeembodiments thereof. Numerous other embodiments, modifications, andvariations within the scope and spirit of the appended claims will occurto persons of ordinary skill in the art from a review of thisdisclosure. For example, one or more of the steps depicted in theillustrative figures may be performed in other than the recited order,and one or more depicted steps may be optional in accordance withaspects of the disclosure.

What is claimed is:
 1. A computing platform, comprising: at least oneprocessor; a communication interface communicatively coupled to the atleast one processor; and memory storing computer-readable instructionsthat, when executed by the at least one processor, cause the computingplatform to: generate, based on input received from a user correspondingto a financial organization, a multi-threaded profile corresponding tothe financial organization, wherein the multi-threaded profile comprisesfinancial information of the user; receive, via the communicationinterface and from a user device, external event information, whereinthe external event information comprises a first big data set comprisingadditional financial information of the user; determine, based on thefirst big data set comprising additional financial information of theuser, a first smart data set corresponding to the multi-threadedprofile, wherein determining the first smart data set corresponding tothe multi-threaded profile comprises determining the first smart dataset corresponding to the multi-threaded profile based on the financialinformation of the user and a determination, by the computing platform,that the additional financial information of the user comprises at leastone of information indicating user purchasing activity or informationindicating user spending activity; determine, based on the first smartdata set, a filter bank corresponding to an exchange thread of themulti-threaded profile; determine, based on the first smart data set andthe filter bank corresponding to the exchange thread, a first time tolive parameter corresponding to the first smart data set; retrieve, froma multi-threaded profile server configured to store multi-threadedprofiles corresponding to the financial organization and based on themulti-threaded profile and the filter bank, exchange thread informationcorresponding to the exchange thread of the multi-threaded profile;determine, based on the exchange thread information, the first smartdata set, and the first time to live parameter, one or morerecommendations for the user; generate one or more commands directingthe user device to display the one or more recommendations for the user;transmit, via the communication interface and to the user device, theone or more commands; determine that the first time to live parametercorresponding to the first smart data set has elapsed; and remove, basedon the determining that the first time to live parameter has elapsed,the first smart data set from the multi-threaded profile.
 2. Thecomputing platform of claim 1, wherein the generating the multi-threadedprofile corresponding to the user comprises: receiving, via thecommunication interface and from an administrative device, new profileinformation corresponding to the multi-threaded profile; and generating,based on the new profile information, a plurality of threads for themulti-threaded profile, wherein each of the plurality of threadsindicates previous interactions corresponding to the user.
 3. Thecomputing platform of claim 2, wherein the plurality of threadscomprises an education thread, a leisure thread, or a hobby thread. 4.The computing platform of claim 1, wherein the memory stores additionalcomputer-readable instructions that, when executed by the at least oneprocessor, further causes the computing platform to: receive, via thecommunication interface and from an external data source, customizationinformation corresponding to the user; and update, based on thecustomization information, the multi-threaded profile corresponding tothe user.
 5. The computing platform of claim 4, wherein thecustomization information comprises social media information orprofessional worksite information corresponding to the user.
 6. Thecomputing platform of claim 1, wherein a second thread of themulti-threaded profile comprises an education thread, a leisure thread,or a hobby thread.
 7. The computing platform of claim 1, wherein thedetermining the one or more recommendations is based on comparing theexchange thread information with the first smart data set.
 8. Thecomputing platform of claim 1, wherein the memory stores additionalcomputer-readable instructions that, when executed by the at least oneprocessor, further causes the computing platform to: update, based onthe first smart data set, the exchange thread information correspondingto the exchange thread of the multi-threaded profile.
 9. The computingplatform of claim 8, wherein the memory stores additionalcomputer-readable instructions that, when executed by the at least oneprocessor, further causes the computing platform to: receive, via thecommunication interface and from the user device, second external eventinformation, wherein the second external event information comprises asecond big data set corresponding to the financial organization;determine, based on the second big data set corresponding to thefinancial organization, a second smart data set corresponding to themulti-threaded profile, wherein determining the second smart data setcorresponding to the multi-threaded profile comprises determining thesecond smart data set corresponding to the multi-threaded profile basedon the financial information of the user and the second big data setcomprising at least one of information indicating user purchasingactivity or information indicating user spending activity; determine,based on the second smart data set, the filter bank corresponding to theexchange thread of the multi-threaded profile; determine, based on thesecond smart data set and the filter bank, a second time to liveparameter corresponding to the second smart data set; retrieve, from themulti-threaded profile server and based on the multi-threaded profileand the filter bank, exchange thread information corresponding to theexchange thread of the multi-threaded profile; determine, based on theexchange thread information, the second smart data set, and the secondtime to live parameter, one or more second recommendations for the user;generate one or more second commands directing the user device todisplay the one or more second recommendations corresponding to thesecond smart data set; and transmit, via the communication interface andto the user device, the one or more second commands.
 10. The computingplatform of claim 1, wherein the financial information of the user isstored in the filter bank corresponding to the exchange thread.
 11. Thecomputing platform of claim 10, wherein the memory stores additionalcomputer-readable instructions that, when executed by the at least oneprocessor, cause the computing platform to: generate one or morecommands, based on receiving a request, from the user device,corresponding to the exchange thread, directing the user device todisplay the financial information of the user.
 12. The computingplatform of claim 10, wherein determining the one or morerecommendations for the user comprises determining the one or morerecommendations for the user further based on the user purchasingactivity of the user, and wherein information corresponding to the userpurchasing activity is stored in the filter bank corresponding to theexchange thread of the multi-threaded profile.
 13. A method, comprising:at a computing platform comprising at least one processor, memory, and acommunication interface: generating, based on input received from abusiness organization associated with a financial organization, amulti-threaded profile corresponding to the financial organization,wherein the multi-threaded profile comprises financial information ofthe business organization; receiving, via the communication interfaceand from a computing device of the business organization, external eventinformation, wherein the external event information comprises a big dataset comprising additional financial information of the businessorganization; determine, based on the big data set comprising additionalinformation of the business organization, a smart data set correspondingto the multi-threaded profile, wherein determining the smart data setcorresponding to the multi-threaded profile comprises determining thesmart data set corresponding to the multi-threaded profile based on thefinancial information of the business organization and a determination,by the computing platform, that the additional financial information ofthe business organization comprises at least one of informationindicating purchasing activity of the business organization orinformation indicating spending activity of the business organization;determining, based on the smart data set, a filter bank corresponding toan exchange thread of the multi-threaded profile; determining, based onthe smart data set and the filter bank corresponding to the exchangethread, a time to live parameter corresponding to the smart data set;retrieving, from a multi-threaded profile server configured to storemulti-threaded profiles corresponding to the financial organization andbased on the multi-threaded profile and the filter bank, exchange threadinformation corresponding to the exchange thread of the multi-threadedprofile; determining, based on the exchange thread information, thesmart data set, and the time to live parameter, one or morerecommendations for the business organization; generating one or morecommands directing the computing device of the business organization todisplay the one or more recommendations for the business organization;transmitting, via the communication interface and to the computingdevice of the business organization, the one or more commands;determining that the time to live parameter corresponding to the smartdata set has elapsed; and removing, based on the determining that thetime to live parameter has elapsed, the smart data set from themulti-threaded profile.
 14. The method of claim 13, wherein thegenerating the multi-threaded profile corresponding to the businessorganization comprises: receiving, via the communication interface andfrom an administrative device, new profile information corresponding tothe multi-threaded profile; and generating, based on the new profileinformation, a plurality of threads for the multi-threaded profile,wherein each of the plurality of threads indicates previous interactionscorresponding to the business organization.
 15. The method of claim 14,wherein the plurality of threads comprises an education thread, aleisure thread, or a hobby thread.
 16. The method of claim 13, furthercomprising: receiving, via the communication interface and from anexternal data source, customization information corresponding to thebusiness organization; and updating, based on the customizationinformation, the multi-threaded profile corresponding to the businessorganization.
 17. The method of claim 16, wherein the customizationinformation comprises social media information or professional worksiteinformation corresponding to the business organization.
 18. The methodof claim 13, wherein a second thread of the multi-threaded profilecomprises an education thread, a leisure thread, or a hobby thread. 19.The method of claim 13, wherein the determining the one or morerecommendations is based on comparing the exchange thread informationwith the smart data set.
 20. The method of claim 13, further comprising:updating, based on the smart data set, the exchange thread informationcorresponding to the exchange thread of the multi-threaded profile. 21.One or more non-transitory computer-readable media storing instructionsthat, when executed by a computing platform comprising at least oneprocessor, memory, and a communication interface, cause the computingplatform to: generate, based on input received from a user correspondingto a financial organization, a multi-threaded profile corresponding tothe financial organization, wherein the multi-threaded profile comprisesfinancial information of the user; receive, via the communicationinterface and from a user device, external event information, whereinthe external event information comprises a big data set comprisingadditional financial information of the user; determine, based on thebig data set comprising additional financial information of the user, asmart data set corresponding to the multi-threaded profile, whereindetermining the smart data set corresponding to the multi-threadedprofile comprises determining the smart data set corresponding to themulti-threaded profile based on the financial information of the userand a determination, by the computing platform, that the additionalfinancial information of the user comprises at least one of informationindicating user purchasing activity or information indicating userspending activity; determine, based on the smart data set, a filter bankcorresponding to an exchange thread of the multi-threaded profile;determine, based on the smart data set and the filter bank correspondingto the exchange thread, a time to live parameter corresponding to thesmart data set; retrieve, from a multi-threaded profile serverconfigured to store multi-threaded profiles corresponding to thefinancial organization and based on the multi-threaded profile and thefilter bank, exchange thread information corresponding to the exchangethread of the multi-threaded profile; determine, based on the exchangethread information, the smart data set, and the time to live parameter,one or more recommendations for the user; generate one or more commandsdirecting the user device to display the one or more recommendations forthe user; transmit, via the communication interface and to the userdevice, the one or more commands; determine that the time to liveparameter corresponding to the smart data set has elapsed; and remove,based on the determining that the time to live parameter has elapsed,the smart data set from the multi-threaded profile.